Changeset 193 for bdm/estim/merger.cpp

Timestamp:

10/22/08 10:46:42 (16 years ago)

Author:

smidl

Message:

oprava merger_iter a jeho casti

Files:

• bdm/estim/merger.cpp (modified) (5 diffs)

bdm/estim/merger.cpp

@@ -60 +60 @@
                 //Re-Initialize Mixture model
                 Mix.init ( &A0, Smp_ex, Nc );
-                Mix.bayesB ( Smp_ex, ones ( Ns ) );//w*Ns );
+                Mix.bayesB ( Smp_ex, w*Ns );
                 Mpred = Mix.predictor ( rv ); // Allocation => must be deleted at the end!!
 
-                // Generate new samples
-                eSmp.set_samples ( Mpred );
-                for ( int i=0;i<Ns;i++ ) {      set_col_part ( Smp_ex,i,Smp ( i ) );}
+                if ( 1 ) {
+                        // Generate new samples
+                        eSmp.set_samples ( Mpred );
+                        for ( int i=0;i<Ns;i++ ) {      set_col_part ( Smp_ex,i,Smp ( i ) );}
+                }
+                else {
+                        for ( int ii=0;ii<10;ii++ ) {
+                                for ( int jj=0; jj<10; jj++ ) {
+                                        Smp ( ii+jj*10 ) =vec_2 ( -1.0+6*ii/10.0, -1.0+6*jj/10.0 );
+                                }
+                        }
+                        for ( int i=0;i<Ns;i++ ) {      set_col_part ( Smp_ex,i,Smp ( i ) );}
+                }
 
                 sprintf ( str,"Mpdf%d",niter );
@@ -98 +108 @@
                                 // Compute likelihood of the missing variable
                                 if ( rv.count() > ( mpdfs ( i )->_rv().count() + mpdfs ( i )->_rvc().count() ) ) {
+                                        ///////////////
+                                        cout << Mpred->mean() <<endl;
                                         // There are variales unknown to mpdfs(i) : rvzs
                                         mpdf* tmp_cond = Mpred->condition ( rvzs ( i ) );
                                         // Compute likelihood
+                                        vec lw_dbg=lw_src;
                                         for ( int k= 0; k<Ns; k++ ) {
                                                 lw_src ( k ) += log (
@@ -111 +124 @@
                                 // Compute likelihood of the partial source
                                 for ( int k= 0; k<Ns; k++ ) {
-                                        mpdfs ( i )->condition ( dls ( i )->get_cond ( Smp(k) ) );
-                                        lw_src ( k ) += mpdfs ( i )->_epdf().evalpdflog ( dls ( i )->get_val ( Smp(k) ) );
+                                        mpdfs ( i )->condition ( dls ( i )->get_cond ( Smp ( k ) ) );
+                                        lw_src ( k ) += mpdfs ( i )->_epdf().evalpdflog ( dls ( i )->get_val ( Smp ( k ) ) );
                                 }
+                                
                         }
                         lW.set_row ( i, lw_src ); // do not divide by mix
@@ -139 +153 @@
                 dbg << Name ( str ) << w;
 
-                eSmp.resample(); // So that it can be used in bayes
-                for ( int i=0;i<Ns;i++ ) {      set_col_part ( Smp_ex,i,Smp ( i ) );}
+//              eSmp.resample(); // So that it can be used in bayes
+//              for ( int i=0;i<Ns;i++ ) {      set_col_part ( Smp_ex,i,Smp ( i ) );}
 
                 sprintf ( str,"Smp_res%d",niter );
@@ -147 +161 @@
                 // ==== stopping rule ===
                 niter++;
-                converged = ( niter>20 );
+                converged = ( niter>4 );
         }